A Systems Theory of Business Intelligence

Information Management Magazine, December 2005

Jerry Kurtyka

Systems theory is one of the main intellectual movements of the 20th century. It arose in response to overspecialization in the sciences as a way to find a more integrated view of knowledge and the world.¹ Systems theory attempts to describe and understand the common structure, attributes and emergent properties of all types of systems - physical, biological and social - by viewing them as systems per se rather than an economy or a business or a machine, for example.

A systems theory of business intelligence (BI) would position BI in the context of its surrounding system - the organizational environment in which it operates - and would predict the impact of that context on BI design. This theory would give designers a tool that guides them on what BI technology can do and what it cannot do in a given environment and the risks involved. In this article, I want to develop a general outline of this tool.

In previous articles in DM Review, I noted that organizations are cognitive systems in dialog with their environment. In order to learn from their experience, organizations collectively need to perform several important cognitive tasks: 1) sense and monitor their environment (e.g., using customer and supplier contact channels); 2) relate the information gained from this to the operating norms that guide the business (e.g., campaign management); 3) detect deviations from these norms; and 4) initiate corrective actions when deviations exceed some preset level. If these tasks are done well, a process of cybernetic information exchange is created between the organization and its overall environment.²

Some pundits describe BI as the cornerstone of this cognitive process, but, as I have shown previously, BI is more accurately described as a technical artifact that encodes a description of the business environment (i.e., the data model).³ BI helps users to understand their environment in terms that are meaningful, such as key performance indicators (KPIs) and dashboards, and facilitates predicting and controlling the business. This is built into the front-end design of the BI system as statements of purpose, scope, functionality, objectives, outputs and so forth, all of which are intended to align the BI system with the organization's strategy.

The problem arises when the organization's environment exhibits a strategy of its own. This happens when the feedback coming in from channels, customers and the larger world (e.g., regulators and competitors) doesn't match the predefined categories of knowledge, queries and other outputs anticipated in the BI system design. If we have designed the BI system to be very specific in the types of data it collects and reports, then its functioning is vulnerable to environmental disturbance. On the other hand, if we are too general in our specifications - the "toolbox" approach - we need to design on the fly for every unique situation. What design approach is right for a given environment?

A Human Systems Model

Let's start with the general human systems model shown in Figure 1 that positions the firm in a larger context, including relationships with its environment and resource base.

The systems view of the world attempts to see individual entities in their larger, connected context; a solution is seen in its relationship to other entities. Thus, when you push at one end of a problem you can anticipate the effects that might happen at another end. This is in contrast to a reductionist view of the world that looks at problems or situations in isolation.

In Figure 1, the firm is seen as a human system in its relationship to:

• The larger world system or the environment in which the firm, its suppliers, competitors, customers and everything are embedded.
• The external environment, i.e., everything that the firm encounters externally in its world and with which it has relationships, but has little control over: customers, regulators, competitors, etc.
• The resource base, i.e., everything that the firm owns, uses or buys (inputs) or has some general control over: labor, capital, suppliers, etc.
• The boundaries of the firm itself that include: 1) business actions consisting of prespecified goals, processes, rules, procedures and actions of the firm; and 2) a business model that includes the physical plant, distribution, organization structure and mental models (presuppositions) within which business actions take place.
• Institutional memory that holds all of this in context and is accessible to the organization's members. BI is a technical artifact of institutional memory but not the entire memory, which is much broader in scope and content.
• Feedback from the environment is the force that drives change. Single-loop feedback only requires that the firm respond by actions within the scope of its current operating framework - there is no revision of the firm's business model, its organization, vision and mission. Double-loop feedback impacts and challenges the firm's more basic assumptions and commitments - resulting in deeper inquiry into experience to examine the basis of the assumptions by which it governs itself, and it may change those assumptions in the process.

Figure 1: General Human Systems Model

The general human systems model of Figure 1 is scalable. For the firm as a whole, it applies to both the immediate environment (i.e., its marketplace and resources) and the larger world system (i.e., its industry). For a given department within the firm, the environment is its user community, and the firm is the larger world system. This is likely to be the case with BI. For the IT department, the BI user is the environment; for the BI user, the environment is likely to be a functional department such as sales, marketing, finance and production.

Positioning BI in the Larger System

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